pro $24.99 per month
- access to all Manning books, MEAPs, liveVideos, liveProjects, and audiobooks!
- choose one free eBook per month to keep
- exclusive 50% discount on all purchases
lite $19.99 per month
- access to all Manning books, including MEAPs!
team
5, 10 or 20 seats+ for your team - learn more
Look inside
Unexpected bias in machine learning models reduces accuracy, produces negative real-world consequences, and in the worst cases, entrenches existing inequalities for decades. Audits that can detect and mitigate this unwanted bias are an essential part of building and maintaining reliable machine learning systems.
In this liveProject, you’ll take on the role of a data scientist running a bias audit for the World Health Organization’s healthcare models. You’ll get to grips with state-of-the-art tools and best practices for bias detection and mitigation, including interpretability methods, the AIF-360 package, and options for imputing membership of a protected class. These tools and practices are placed in the context of a broad universe of bias where geopolitical awareness and deep understanding of the history and use of your particular data is key.
In this liveProject, you’ll take on the role of a data scientist running a bias audit for the World Health Organization’s healthcare models. You’ll get to grips with state-of-the-art tools and best practices for bias detection and mitigation, including interpretability methods, the AIF-360 package, and options for imputing membership of a protected class. These tools and practices are placed in the context of a broad universe of bias where geopolitical awareness and deep understanding of the history and use of your particular data is key.
This project is designed for learning purposes and is not a complete, production-ready application or solution.
prerequisites
The liveProject is for intermediate Python programmers with experience in data science. To begin this liveProject you need to be familiar with:TOOLS
- Basics of pandas
- Basics of scikit-learn
- Basics of Jupyter Notebook
TECHNIQUES
- Classification and regression using random forests and gradient boosting machines
features
- Self-paced
- You choose the schedule and decide how much time to invest as you build your project.
- Project roadmap
- Each project is divided into several achievable steps.
- Get Help
- While within the liveProject platform, get help from fellow participants and even more help with paid sessions with our expert mentors.
- Compare with others
- For each step, compare your deliverable to the solutions by the author and other participants.
- book resources
- Get full access to select books for 90 days. Permanent access to excerpts from Manning products are also included, as well as references to other resources.
related titles
related titles
choose your plan
pro
monthly
annual
$24.99
$249.99
only $20.83 per month
- access to all Manning books, MEAPs, liveVideos, liveProjects, and audiobooks!
- choose another free product every time you renew
- choose twelve free products per year
- exclusive 50% discount on all purchases
-
![]()
Mitigate Machine Learning Bias: A Health Data Project project for free
Mitigate Machine Learning Bias: A Health Data Project project for free
team
monthly
annual
$49.99
$399.99
only $33.33 per month
- five seats for your team
- access to all Manning books, MEAPs, liveVideos, liveProjects, and audiobooks!
- choose another free product every time you renew
- choose twelve free products per year
- exclusive 50% discount on all purchases
-
![]()
Mitigate Machine Learning Bias: A Health Data Project project for free
